Spartan is a library for distributed array programming. Programmers build up array expressions (using Numpy-like operations). These expressions are then compiled and optimized and run on a distributed array backend across multiple machines.
Check out the tutorial on the wiki.
pip install [--user] spartan
# For numpy and scipy, we suggest you use binary install to
# get better performance.
apt-get install python-numpy python-scipy libzmq3-dev
pip install --user dsltools
pip install --user pyzmq
pip install --user cython
pip install --user parakeet
pip install --user scikit-learn
pip install --user traits
git clone https://github.com/spartan-array/spartan.git
cd spartan
python setup.py develop --user
Operations in Spartan look superficially like numpy array operations, but actually are composed into a deferred expression tree. For example:
>> In [3]: x = spartan.ones((10, 10))
>> In [4]: x
MapExpr {
local_dag = None,
fn_kw = DictExpr {
vals = {}
},
children = ListExpr {
vals = [
[0] = NdArrayExpr {
combine_fn = None,
dtype = <type 'float'>,
_shape = (10, 10),
tile_hint = None,
reduce_fn = None
}
]
},
map_fn = <function <lambda> at 0x3dbae60>
}
Expressions are combined together lazily until they are forced -- this
is caused by a call to the force method.
Tests can be run using nosetests pip install --user nose.
pip install --user nose
nosetests tests/
There are a few benchmarks for performance testing, see
tests/benchmark_*.py
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